What are ontologies in AI?
An ontology at its most abstract is a model of the world. It describes concepts that exist in the world and how those concepts are related.
Ontologies are similar to taxonomies. A taxonomy is a tree-like hierarchy that organizes concepts in increasing levels of specificity. What an ontology adds is a second type of link between those concepts that explains how they are connected. So a taxonomy could say $isA(DOG, ANIMAL)$ (&quot;a dog is an animal&quot;). An ontology may also describe something like: $chase(DOG, CAT)$ (&quot;dogs chase cats&quot;).
Why use an ontology? It can be used to reason about the world. I subscribe to a very particular kind of language-centric ontology that isn't worth addressing here. Instead, the Semantic Web project (Tim Berners-Lee) is probably closer to what would interest you. Semantic Web uses a type of description logic, which is outside my realm of expertise. But there are tools for processing these kinds of DL and gaining &quot;understanding&quot; from them. To work with this kind of ontology you'll want to be familiar with the idea of Resource Description Framework triples.